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Glama

find_charging_station

Read-onlyIdempotent

Find EV charging stations near any place or coordinates, showing connector types, power, price, and live availability. Use when a driver needs to locate a charging point.

Instructions

Returns EV charging sites near a place or coordinate with operator, connector types, maximum power, price per kWh where published, and how many points are free right now where the operator publishes live status. Use when an EV driver asks where to charge ("Wo kann ich laden?", "CCS 150 kW near Leipzig", "ist gerade eine Säule frei?"). Do NOT use for petrol or diesel — call find_cheapest_fuel; for E-Kennzeichen or Ladekarte rules — call get_driving_rules. Radius ≤ 25 km, ≤ 10 sites; availability is missing for most operators and is then unknown, never free. Show the attribution line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude in WGS 84, e.g. 48.137. Use with lon when the caller already holds coordinates; otherwise use place.
lonNoLongitude in WGS 84, e.g. 11.576. Use with lat; otherwise use place.
limitNoHow many charging sites to return, nearest first (1–10, default 5).
placeNoWhere to look, as free text: a city ("München", "Munich"), a district or Kreis ("Kreis Fulda"), a Bundesland, a station or stop ("Hamburg Hbf"), a motorway ("A7"), or a street address with a house number ("Hauptstraße 12, 36037 Fulda"). Use this instead of coordinates whenever the person named a place. An address needs its town or postcode — a street and a number alone exist in many towns. Give either place OR lat+lon, never both.
languageNoSet this on every call to the language the person is writing in: "en" if they wrote English, "de" if they wrote German. Do not leave it out because it has a default — the default is only the fallback when the language is genuinely unclear, and an English question answered in German is a wrong answer. Place names, station names and road numbers are never translated in either language; in English the German term is kept in parentheses so the person recognises it on signs and in local apps.de
connectorNoPlug the car needs: "ccs2" (CCS Combo 2 — the DC fast-charging standard on almost every European EV), "type2" (Typ 2 / Mennekes, the AC socket) or "chademo" (older Japanese DC, e.g. Nissan Leaf). Omit unless the person named their plug or their car model — filtering on a guess hides chargers they could have used.
radius_kmNoSearch radius around the place in kilometres (1–25, default 10). A charging stop is worth a detour, so this is wider than the fuel radius — but 25 km is the cap, and a larger circle is a dataset request rather than a driver's question.
min_power_kwNoOnly charging points of at least this many kW (1–1000). Use when the person asks for fast charging or names a number: 50 = DC fast, 150 = HPC, 300 = the fastest posts in Germany. Omit for "where can I charge" — 11 kW overnight is a valid answer to that question.
only_availableNoWhen true, return only sites with at least one point reported FREE right now. Default false. Use it when the person asks what is free at this moment. Note that only some operators publish live status: the result always says how many nearby sites were dropped because their status is unknown, so the filter never silently hides a charger that may well be free.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.9

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool as read-only, idempotent, and non-destructive; the description adds non-obvious behavior: availability is missing for most operators and must be treated as unknown rather than free, and the caller must show the attribution line. These caveats materially affect how an agent should interpret and present results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place: core deliverable, when to use, explicit exclusions, and operational caveats. The most important information is front-loaded, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter tool with no output schema, the description plus schema covers what an agent needs: return fields, selection criteria, anti-selection, constraints, data caveats, and required attribution. Exact response formatting is not necessary for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all 9 parameters in detail. The description adds only cross-cutting caveats (radius/limit caps, availability semantics) but no new per-parameter meaning, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence names the exact deliverable — EV charging sites near a place or coordinate — and lists the key fields returned (operator, connector types, max power, price, live availability). This is a specific verb-resource pairing that easily distinguishes it from find_cheapest_fuel and find_parking.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use triggers with real query examples ('Wo kann ich laden?', 'CCS 150 kW near Leipzig') and explicit when-not-to-use routing to find_cheapest_fuel for petrol/diesel and get_driving_rules for E-Kennzeichen/Ladekarte rules. It also states hard constraints like radius ≤ 25 km and ≤ 10 sites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.